Machine Learning Using Python

Get ready to dive into the world of Machine Learning (ML) using Python! This course is for you, whether you want to advance your career in Data Science or start learning Machine Learning and Deep Learning. This course will start with a light introduction to Machine Learning and what it is all about, covering topics like supervised and unsupervised learning, linear and nonlinear regression, simple regression, and more. You will then dive into classification methods using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and logistic regression. You will also learn about the importance and different types of clustering, such as k-means, hierarchical clustering, and DBSCAN. With all the variety of concepts you will learn, there will be a strong focus on hands-on learning. You will work with Python libraries like SciPy and scikit-learn, and apply your knowledge in labs. In the final project, you will demonstrate your skills by building, evaluating, and comparing several machine learning models using different algorithms. By the end of the course, you will have job-ready skills to add to your resume and a machine learning certificate to prove your expertise.